Several Interdisciplinary Phd Positions
vor 4 Wochen
The Heidelberg Graduate School of Mathematical and Computational Methods for the Sciences ( HGS MathComp ) at Heidelberg University is the leading graduate school in Germany that focuses on the complex topic of Scientific Computing. Located in a vibrant research environment, the school offers a uniquely structured interdisciplinary education for PhD students. HGS MathComp has
**18 open PhD positions** in the general research areas of Mathematics, Computer Science, Physics, Biology, Chemistry, and Life Sciences.
**Scope and duration of the PhD positions**:
- Three-year contract with the possibility of extension
- Salary according to TV-L E13 level; contract details depend on research project
- Faculty/department affiliation according to research group
- Start: October 1, 2023, unless otherwise stated below
- Application details: see bottom of page
**PhD positions are available for the following PhD project topics**:
Immersed interface methods for the simulation of cell movement
- Research group: Mathematical Methods of Simulation
- Supervisor: Prof. Dr. Guido Kanschat
- Start: Position available immediately
- Additional information: Joint project with Prof. Dr. Christine Selhuber-Unkel at IMSEAM; depending on focus, Dr. rer. nat. or Dr-Ing. possible
**Multiscale Methods and Localized Model Reduction for Convection-Dominated Problems and Applications in Climate Modelling**
- Research group: Numerical Analysis and Uncertainty Quantification
- Supervisor: Prof. Dr. Robert Scheichl
- Additional information: In collaboration with Prof. Dr. Jörn Behrens and Dr. Sanam Vardag.
**Modeling and simulation of thermochemical energy conversion processes for the flexible use of hydrogen-based renewable fuels**
- Research group: Multiphase Flows and Combustion
- Supervisor: Prof. Dr. Eva Gutheil
- Start: September 16 or October 1, 2023
**Transformer-based cell tracking in virology**
- Research group: Image Analysis and Learning
- Supervisor: Prof. Dr. Fred Hamprecht
- Start: Position available immediately
**Geometric machine learning in quantum chemistry: learning kinetic energy density functionals**
- Research group: Image Analysis and Learning
- Supervisor: Prof. Dr. Fred Hamprecht
- Start: Position available immediately
- Additional information: If successful, this project will enable a breakthrough in the computational cost of quantum chemical calculations. A solid understanding of quantum mechanics and machine learning are required. We are a small and friendly team and work on this exciting project together with the lab of Prof. Dr. Andreas Dreuw in the simplaix consortium.
**Modelling cytoadhesion of malaria-infected red blood cells**
- Research group: Schwarz group, theoretical biophysics
- Supervisor: Prof. Dr. Ulrich Schwarz
- Start: Position available immediately
- Additional information: A background in hydrodynamics and/or molecular dynamics would be helpful. This project is funded by SFB 1129 (integrative analysis of pathogen replication and spread).
**Traction force microscopy for biological cells in three dimensions**
- Research group: Schwarz group, theoretical biophysics
- Supervisor: Prof. Dr. Ulrich Schwarz
- Start: Position available immediately
- Additional information: A background in continuum mechanics and inverse problems would be helpful. This project is funded by the excellence cluster 3DMM2O.
**Domain Uncertainty Quantification**
- Research group: UQ and Scientific Machine Learning
- Supervisor: Jun. Prof. Dr. Jakob Zech
- Additional information: Applicants should possess a strong background in mathematics, ideally with a focus on PDEs. Experience with machine learning is also highly beneficial. Postdocs are welcome.
**Machine Learning for Programming (2 PhD positions)**
- Research group: Parallel and Distributed Systems (PVS)
- Supervisor: Prof. Dr. Artur Andrzejak
- Start: September 1 or October 1, 2023 for one position, later start possible for second position
- Additional information: Research fields are ML/AI-based approaches for code-to-code translation, vulnerability detection, performance optimization, and AI-assisted programming. Background and experience in deep learning for NLP and/or source code analysis are a plus. Postdocs are welcome. Very good command of the German language is a requirement for at least one of these positions.
**Model based AI: Physics Informed Neural Networks (fundamental research)**
- Research group: Data Analysis and Modeling in Medicine
- Supervisor: Prof. Dr. Jürgen Hesser
- Additional information: Background in mathematics with experience in machine learning and PDEs or computer science with good background in machine learning (ideally physics informed neural networks) but also with a good math background
**Machine Learning and Model-based controller (applied research)**
- Research group: Data Analysis and Modeling in Medicine
- Supervisor: Prof. Dr. Jürgen Hesser
- Additional information: Background in machine learning (must) and model-based
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